We are thrilled to announce the latest release of our Python Connectors product line, now featuring a subscription model designed to offer even greater cost-effectiveness and convenience. The new pricing structure makes our connectors more accessible, allowing users to benefit from ongoing updates and support while optimizing their software expenditure.
With this release, we:
Roll out a brand new Python Connector for Microsoft Excel
Introduce new subscription model
Add connection pooling
Implement metadata caching for cloud connectors
Expand compatibility options
Python Connector for Microsoft Excel
The newly released Python Connector for Microsoft Excel is a robust solution for accessing Microsoft Excel databases from Python applications. It enables users to perform create, read, update, and delete operations on their Microsoft Excel data. Compliant with the Python DB API 2.0 specification, the Python Connector for Microsoft Excel is distributed as a wheel package for Windows, macOS, and Linux, ensuring seamless integration and flexibility across various platforms.
New subscription model
We are excited to introduce our new subscription model, which shifts from a one-time upfront payment to an annual fee for accessing our Python Connectors and associated services. This change aims to make our products more accessible and financially manageable for users. At the heart of this update is our commitment to providing ongoing value and support to our customers, ensuring they have the tools and resources they need to succeed.
Connection pooling
In this release, we have introduced connection pooling across all connectors, improving the speed of reconnecting to databases. Connection pooling significantly reduces the cost of opening and closing connections by maintaining a pool of pre-established connections to a database or cloud service. This enhancement allows for more efficient resource management and faster access times.
Connection pooling configuration is quite flexible:
devart.oracle.connection_pool.min_size = 0
devart.oracle.connection_pool.max_size = 100
devart.oracle.connection_pool.lifetime = 60000
devart.oracle.connection_pool.validate = True
devart.oracle.connection_pool.enabled = TrueIf you want to enable pooling with default settings, you can do that with one line of code:
devart.oracle.connection_pool.enabled = TrueMetadata caching
Additionally, we’ve implemented metadata caching for our Python Connectors for BigCommerce, Dynamics 365, NetSuite, Salesforce, and Zoho CRM. This improvement speeds up interactions with metadata from these data sources, enhancing overall performance and reducing latency.
New compatibility options
The release also introduces several key compatibility enhancements:
- Support for Firebird 5
- Support for PostgreSQL 16
- Support for MongoDB 6 and 7
- Support for UTF-8 Encoding in xBase
This release highlights our dedication to offering powerful, efficient, and up-to-date solutions for our users. We invite you to download and explore our updated connectors to take full advantage of these new features and improvements.
Full list of our Python Connectors
